Quasi-Exact Cubature of the Bivariate Normal Density
The bivariate Gaussian density can be integrated based on a triangulation of
the (transformed) polygonal domain, using formulae from the
Abramowitz and Stegun (1972) handbook (Section 26.9, Example 9, pp. 956f.).
This method is quite cumbersome because the A&S formula is only for triangles
where one vertex is the origin (0,0). For each triangle of the
tristrip we have to check in which of the 6 outer
regions of the triangle the origin (0,0) lies and adapt the signs in the
formula appropriately: (AOB+BOC-AOC) or (AOB-AOC-BOC) or
(AOB+AOC-BOC) or (AOC+BOC-AOB) or ....
However, the most time consuming step is the
evaluation of pmvnorm.
polyCub.exact.Gauss(polyregion, mean = c(0, 0), Sigma = diag(2), plot = FALSE)
| polyregion | a  | 
| mean, Sigma | mean and covariance matrix of the bivariate normal density to be integrated. | 
| plot | logical indicating if an illustrative plot of the numerical
integration should be produced. Note that the  | 
The integral of the bivariate normal density over polyregion.
Two attributes are appended to the integral value:
| nEval | number of triangles over which the standard bivariate normal density had to
be integrated, i.e. number of calls to  | 
| error | Approximate absolute integration error stemming from the error introduced by
the  | 
The package gpclib is required to produce the
tristrip, since this is not implemented in rgeos
(as of version 0.3-25).
The restricted license of gpclib (commercial use prohibited)
has to be accepted explicitly via
gpclibPermit() prior to using polyCub.exact.Gauss.
Abramowitz, M. and Stegun, I. A. (1972). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. New York: Dover Publications.
circleCub.Gauss for quasi-exact cubature of the
isotropic Gaussian density over a circular domain.
Other polyCub-methods: 
polyCub.SV(),
polyCub.iso(),
polyCub.midpoint(),
polyCub()
## a function to integrate (here: isotropic zero-mean Gaussian density)
f <- function (s, sigma = 5)
    exp(-rowSums(s^2)/2/sigma^2) / (2*pi*sigma^2)
## a simple polygon as integration domain
hexagon <- list(
    list(x = c(7.33, 7.33, 3, -1.33, -1.33, 3),
         y = c(-0.5, 4.5, 7, 4.5, -0.5, -3))
)
## quasi-exact integration based on gpclib::tristrip() and mvtnorm::pmvnorm()
if (requireNamespace("mvtnorm") && gpclibPermit()) {
    hexagon.gpc <- new("gpc.poly", pts = lapply(hexagon, c, list(hole = FALSE)))
    plotpolyf(hexagon.gpc, f, xlim = c(-8,8), ylim = c(-8,8))
    print(polyCub.exact.Gauss(hexagon.gpc, mean = c(0,0), Sigma = 5^2*diag(2),
                              plot = TRUE), digits = 16)
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